Many popular image and video compression standards, such as JPEG and MPEG2, are based on Discrete Cosine Transform (DCT) processing. The basic approach of the DCT-based image and video compression technique is to subdivide the image into 8×8 blocks and then individually transform, quantize, and encode each block. In DCT-based compression techniques artifacts may occur, specially at low and moderate bit rates. Among several well-known artifacts, one is typically known as mosquito noise or ringing noise, which mostly appears in image homogeneous regions near strong edges. Mosquito noise is caused by loss of high frequency transform coefficients during the quantization step.
In recent years, several techniques have been proposed for mosquito noise reduction. Generally speaking, there are two types of techniques for mosquito noise reduction. One uses coding parameters to control the filtering process. The other does not rely on the coding information, and is usually called post-processing. The first type techniques require the decoder to send out some coding parameters along with the decoded video sequence, which in many practical situations are impossible. As such, applications for the first type of noise reduction techniques are limited. The second type techniques usually apply some adaptive filtering methods in order to avoid damaging image structures. Among the second type techniques, a technique proposed in the patent application WO 02/102086 uses a segmentation map to guide the filtering process. It classifies the image into five regions and assigns different regions with different filtering weights. FIG. 1 shows a block diagram of the image classifier 100 used in this method. However, classifying the image into five regions and using several cascaded filters, increases hardware complexity and cost.